Enhancements in Estimation of Daily Modal Shares for Cities

This contribution describes an approach to estimate modal shares in the city of Cologne on a daily basis which is in contrast to travel demand surveys typically used, which are conducted in frequencies of many years. To accomplish this, the approach uses a diverse set of input data which are often available in cities: most notably the complete data-base of all traffic detectors in Cologne (loop detectors, but also pedestrian and public transport activation, and dedicated bicycle counters) and the data from a mobile phone provider. These data sets are cleaned, merged, and then used to estimate the daily number of trips by foot, bicycle, car, and public transport, respectively. While the methods and algorithms which are used have already been published, this contribution presents results of the meanwhile three-year application period as well as enhancements of the estimation by using georeferenced information of all data and sensors for calculating region-dependent estimations for different sub regions of Cologne.